UCR time series anomaly archive (UCR). It has been recently proposed by Renjie and Keogh [1]}. In [1]}, the authors claim that most of the existing anomaly detection datasets are trivial. By trivial, they mean that an anomaly can be detected with a single line of MATLAB code. They also criticize the lack of realism and annotation precision in current datasets. As an alternative, they introduce the UCR dataset, which gathers 250 realistic sub-datasets. This dataset is collected from various fields, including medicine, sports, and robotics. The training and test sets are well-definedMore information about the UCR dataset can be found here.
